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Field
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development of future proposals for funding, into AI for renewable energy. You will consider ways in which the integration of machine learning algorithms might support the wider integration of, and uptake
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learning, and data science, with a particular focus on neuroscience applications. Designs AI techniques and algorithms for multimodal data fusion (e.g., MRI, EEG, cognitive and behavioral data, blood
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for trust and authenticity, perceptions of AI and algorithms in digital information environments, news and technology in everyday life, differences in attitudes to AI between journalists and audiences
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algorithms in digital information environments, news and technology in everyday life, differences in attitudes to AI between journalists and audiences, or experiences and understandings amongst different
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programming and data analysis. Interest in developing methods, algorithms or software. Evidence of publications in high-quality peer-reviewed journals. Excellent communication skills. Experience
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are looking for junior scientists who are especially interested in working at the intersection of systems and algorithmic theory, in areas such as programmable network architectures, data center network
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are looking for junior scientists who are especially interested in working at the intersection of systems and algorithmic theory, in areas such as programmable network architectures, data center network
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to research-based activities, including the development of new data analysis algorithms, processing and analysis of field data, and participation in the fieldwork. Your responsibilities will include: Conduct
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efficient algorithms with provable statistical guarantees, using tools from: high-dimensional statistics, optimization, probability theory, etc. These positions would be especially relevant for those with a
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develop algorithms to identify and predict SRL subprocesses from multimodal learning data (e.g., EEG/fNIRS, eye-tracking, and think-aloud protocols); • Analyze large-scale learning analytics data